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Computational Statistics and Machine Learning
A Sparse Approach
Seiten
2019
Wiley-Blackwell (Verlag)
978-0-470-97356-1 (ISBN)
Wiley-Blackwell (Verlag)
978-0-470-97356-1 (ISBN)
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This book focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L-0 norm minimization using greedy algorithms and considers the set covering machines, matching pursuit algorithms in machine learning, and random projection methods.
Computational Statistics and Machine Learning: A Sparse Approach focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L-0 norm minimization using greedy algorithms and considers the set covering machines, matching pursuit algorithms in machine learning, and random projection methods. The second part, which addresses L-1 norm minimization, discusses linear programming boosting, LASSO/LARS, and compressed sensing. All chapters include a detailed description of algorithms and pseudo-code and, where appropriate, a theoretical analysis of generalization ability motivating the use of sparsity. A final chapter covers applications.
Computational Statistics and Machine Learning: A Sparse Approach focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L-0 norm minimization using greedy algorithms and considers the set covering machines, matching pursuit algorithms in machine learning, and random projection methods. The second part, which addresses L-1 norm minimization, discusses linear programming boosting, LASSO/LARS, and compressed sensing. All chapters include a detailed description of algorithms and pseudo-code and, where appropriate, a theoretical analysis of generalization ability motivating the use of sparsity. A final chapter covers applications.
Erscheint lt. Verlag | 29.11.2019 |
---|---|
Reihe/Serie | Wiley Series in Probability and Statistics |
Verlagsort | Hoboken |
Sprache | englisch |
Maße | 152 x 229 mm |
Themenwelt | Mathematik / Informatik ► Mathematik |
Naturwissenschaften ► Biologie | |
Technik ► Elektrotechnik / Energietechnik | |
ISBN-10 | 0-470-97356-0 / 0470973560 |
ISBN-13 | 978-0-470-97356-1 / 9780470973561 |
Zustand | Neuware |
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